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SoftwareInformation Industrial Revolution in The Creative Technology

Intelligent Information Processing Laboratory

Harukazu Igarashi

Professor, Department of Information Science and Engineering
College of Engineering
Electrical Engineering and Computer Science in Master's Program
Functional Control Systems in Doctoral Program
Location: Toyosu Campus

Laboratory Overview

Reinforcement Learning and Multiagent system

We do research on reinforcement learning and its application to multiagent systems. Reinforcement learning make agent's policies by intensifying and supressing action rules through rewards and penalties given to agent's try and error processes. A mutiagent system is a set of agents that interact with each other and applied to designing intelligent systems.

Laboratory Character

Mutiagent systems are drawing attention of researchers to design intelligent contorolling systems in many research fields. Reinforcement learning is very appropriate to make agents learn or adapt to new environments that change dynamically. It is used to make intelligent game programs in Chess, Go and Shogi.

Velocity control of a car based on Fuzzy control and reinforcement learning

Affiliated Conferences

The Japanese Society for Artificial Intelligence

Information Processing Society of Japan

The Institute of Electronics

Information and Communication Engineers

For Social Contributions to the World Sustainability

In future years, our research will contribute to system management of multiple robots and computers collaborating with each other. An example of its application is a scheduling system that controls automatic guided vehicles safely and effectively.